Script 915: Bidding Strategy Assignment

Purpose

The script automates the assignment of a bidding strategy to campaigns based on their creation date, switching from a “Data Gathering” strategy to a “Performance Bidding” strategy after seven days.

To Elaborate

The Python script is designed to manage and automate the assignment of bidding strategies for advertising campaigns. It initially assigns a campaign to an “Impression Share Strategy” called “Data Gathering” for the first seven days after the campaign’s creation. After this period, the campaign is transitioned to a “CPA strategy” known as “Performance Bidding.” The script checks the creation date of each campaign and determines the appropriate strategy based on whether the campaign is within seven days of its creation date. If it is within this timeframe, the campaign is assigned to “Data Gathering” with a blank entry in the “Folder Check” column. If the campaign is older than seven days, it is assigned to “Performance Bidding,” and the “Folder Check” column is marked with “YES.”

Walking Through the Code

  1. Data Preparation
    • The script begins by copying the input DataFrame to ensure the original data remains unchanged.
    • It converts the ‘Campaign Creation Date’ column from string format to datetime objects for accurate date comparisons.
  2. Strategy Assignment Logic
    • The script iterates over each row in the DataFrame to evaluate the campaign’s creation date.
    • If the campaign is created within the last seven days, it assigns the “Data Gathering” strategy and leaves the “Folder Check” column blank.
    • For campaigns older than seven days, it assigns the “Performance Bidding” strategy and marks the “Folder Check” column with “YES.”
  3. Output and Debugging
    • The script prints the changes made to the DataFrame, specifically the ‘Account’, ‘Campaign’, ‘Strategy’, and ‘Folder Check’ columns, to verify the correct assignment of strategies.
    • Finally, the modified DataFrame is returned as the output.

Vitals

  • Script ID : 915
  • Client ID / Customer ID: 1306926015 / 69058
  • Action Type: Bulk Upload
  • Item Changed: Campaign
  • Output Columns: Account, Campaign, Strategy, Folder Check
  • Linked Datasource: M1 Report
  • Reference Datasource: None
  • Owner: Jeremy Brown (jbrown@marinsoftware.com)
  • Created by Jeremy Brown on 2024-04-11 09:01
  • Last Updated by Jeremy Brown on 2024-04-11 09:01
> See it in Action

Python Code

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##
## name: Bidding Strategy Assignment
## description:
##
## The Script automatically assigns a campaign to an Impression Share Strategy called 'Data Gathering' for the first 7 days after being created. Then after the campaign has been live for 7 days it is moved to a CPA strategy called 'Performance Bidding'. The logic is as follows;
## When a campaign's creation date is within 7 days of today's date, it is assigned to "Data Gathering" with a blank Folder Check column (""). Otherwise, it's assigned to "Performance Bidding" with a "YES" in the Folder Check column.
## 
## author: Jeremy Brown
## created: 2024-04-11
## 

today = datetime.datetime.now(CLIENT_TIMEZONE).date()

# primary data source and columns
inputDf = dataSourceDict["1"]
RPT_COL_CAMPAIGN = 'Campaign'
RPT_COL_ACCOUNT = 'Account'
RPT_COL_PUBLISHER = 'Publisher'
RPT_COL_STRATEGY = 'Strategy'
RPT_COL_CAMPAIGN_CREATION_DATE = 'Campaign Creation Date'
RPT_COL_FOLDER_CHECK = 'Folder Check'
RPT_COL_IMPR = 'Impr.'

def process(inputDf):
    # Make a copy of the input DataFrame
    outputDf = inputDf.copy()
    
    # Get today's date in the specified timezone
    today_date = datetime.datetime.now(CLIENT_TIMEZONE).date()
    
    # Convert 'Campaign Creation Date' column to datetime objects (assuming format dd/mm/yyyy)
    outputDf['Campaign Creation Date'] = pd.to_datetime(outputDf['Campaign Creation Date'], format='%d/%m/%Y')
    
    # Determine the strategy and folder check based on the campaign creation date
    for index, row in outputDf.iterrows():
        creation_date = row['Campaign Creation Date'].date()
        if (today_date - creation_date).days <= 7:
            # Within 7 days of today's date
            outputDf.at[index, 'Strategy'] = "Data Gathering"
            outputDf.at[index, 'Folder Check'] = ""  # Leave Folder Check blank
        else:
            # More than 7 days old
            outputDf.at[index, 'Strategy'] = "Performance Bidding"
            outputDf.at[index, 'Folder Check'] = "YES"
    
    # Debugging: Print changes made to outputDf
    print("Data Changed:")
    print(outputDf[['Account', 'Campaign', 'Strategy', 'Folder Check']])
    
    return outputDf

# Example usage:
# Assuming inputDf is your actual DataFrame with the appropriate columns
# inputDf = ...

# Process the DataFrame
outputDf = process(inputDf)

Post generated on 2024-11-27 06:58:46 GMT

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